On testing for structural break of coefficients in factor-augmented regression models

DOI10.1016/j.econlet.2017.10.001zbMath1401.62229OpenAlexW2766387077MaRDI QIDQ1786799

Sanpan Chen, Guowei Cui, Zhang, Jianhua

Publication date: 25 September 2018

Published in: Economics Letters (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/j.econlet.2017.10.001

zbMATH Keywords

asymptotic null distributionfactor-augmented regression modelstructural break test

Mathematics Subject Classification ID

Applications of statistics to economics (62P20) Factor analysis and principal components; correspondence analysis (62H25) Time series, auto-correlation, regression, etc. in statistics (GARCH) (62M10)

Cites Work

• Heteroskedasticity and Autocorrelation Consistent Covariance Matrix Estimation
• Detecting big structural breaks in large factor models
• Factor-augmented regression models with structural change
• Identification and estimation of a large factor model with structural instability
• Testing for structural breaks in dynamic factor models
• Estimation of heterogeneous panels with structural breaks
• Testing for structural stability of factor augmented forecasting models
• Consistent factor estimation in dynamic factor models with structural instability
• Tests for Parameter Instability and Structural Change With Unknown Change Point
• Confidence Intervals for Diffusion Index Forecasts and Inference for Factor-Augmented Regressions
• TESTS FOR PARAMETER INSTABILITY IN DYNAMIC FACTOR MODELS
• Optimal Tests when a Nuisance Parameter is Present Only Under the Alternative
• Forecasting Using Principal Components From a Large Number of Predictors
• Estimating and Testing Linear Models with Multiple Structural Changes
• CRITICAL VALUES AND P VALUES OF BESSEL PROCESS DISTRIBUTIONS: COMPUTATION AND APPLICATION TO STRUCTURAL BREAK TESTS
• Shrinkage Estimation of High-Dimensional Factor Models with Structural Instabilities
• Inferential Theory for Factor Models of Large Dimensions
• Determining the Number of Factors in Approximate Factor Models

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